Spam & Fake Reviews

Social media abuse, including spam, harassment, and fake reviews have become a ubiquitous problem for social media and ecommerce companies, with reports indicating 47% of social media users the subject of online abuse and Facebook deleting 866M spam posts in the first quarter of 2018 alone. Spammers and fraudsters can easily circumvent rules engines or supervised machine learning solutions with sophisticated attack techniques. DataVisor’s Unsupervised Machine Learning Engine provides the next level of defense against these sophisticated techniques by analyzing the hidden connections between accounts. It detects new and evolving attacks without training data or labels, and often before the spam or fake reviews have been sent.

IP Obfuscation

Why UML Can Stop Sophisticated Social Media Abuse

DataVisor’s Unsupervised Machine Learning Engine is uniquely capable of stopping sophisticated, evolving social media abuse because it analyzes all accounts and events at once, uncovering the hidden connections between them. This approach allows DataVisor to detect spam or fake reviews without training data or labels, and even when individual accounts do not appear suspicious when viewed in isolation.

Detect Unknown Threats

Detect new and continually evolving attacks faster, without waiting for training data or labels.

Accuracy and Coverage

Analyze hidden connections between accounts to detect more attacks while lowering false positives.

Early Detection

Detect malicious accounts at account registration before they can send spam or publish fake reviews.

Watch this recording of a webinar hosted by Julian Wong, Technical Architect at DataVisor, and his special guest, Jim Blomo, Director of Engineering at Yelp, to learn how Yelp stops fake users while connecting people with local businesses.

The DataVisor Platform

Unsupervised Machine Learning Engine

Predict new, unknown threats without labels or training data by analyzing hundreds of millions of accounts and events simultaneously using the industry’s most advanced unsupervised learning technology.

What’s Happening with Spam & Fake Reviews

The DataVisor Online Fraud Report took a look at our base of more than one billion users across 172+ countries in the world. Using this massive amount of data, we were able to identify some of the favorite tools and attack techniques that online criminals from around the globe favor when doing their dirty work.

Social spam is not new. We’ve all experienced our share of unsolicited comments, stranger friend requests, phishing links, fake reviews, and click-baiting. But as online services introduce new features to make connecting and sharing

We are entering an era of billions of users and trillions of online accounts. This is attracting a growing wave of attacks like fake reviews targeting online services of all sizes. The Internet user population